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                <h1 class="post-title" itemprop="name headline"> [Python3网络爬虫开发实战] 14.2–Scrapy-Redis 源码解析 </h1>
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                <h1 id="14-2-Scrapy-Redis-源码解析"><a href="#14-2-Scrapy-Redis-源码解析" class="headerlink" title="14.2 Scrapy-Redis 源码解析"></a>14.2 Scrapy-Redis 源码解析</h1>
                <p>Scrapy-Redis 库已经为我们提供了 Scrapy 分布式的队列、调度器、去重等功能，其 GitHub 地址为：<a href="https://github.com/rmax/scrapy-redis" target="_blank" rel="noopener">https://github.com/rmax/scrapy-redis</a>。 本节我们深入了解一下，利用 Redis 如何实现 Scrapy 分布式。</p>
                <h3 id="1-获取源码"><a href="#1-获取源码" class="headerlink" title="1. 获取源码"></a>1. 获取源码</h3>
                <p>可以把源码克隆下来，执行如下命令：</p>
                <figure class="highlight crmsh">
                  <table>
                    <tr>
                      <td class="gutter">
                        <pre><span class="line">1</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line">git <span class="keyword">clone</span> <span class="title">https</span>://github.com/rmax/scrapy-redis.git</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>核心源码在 scrapy-redis/src/scrapy_redis 目录下。</p>
                <h3 id="2-爬取队列"><a href="#2-爬取队列" class="headerlink" title="2. 爬取队列"></a>2. 爬取队列</h3>
                <p>从爬取队列入手，看看它的具体实现。源码文件为 queue.py，它有三个队列的实现，首先它实现了一个父类 Base，提供一些基本方法和属性，如下所示：</p>
                <figure class="highlight python">
                  <table>
                    <tr>
                      <td class="gutter">
                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">Base</span><span class="params">(object)</span>:</span></span><br><span class="line">    <span class="string">"""Per-spider base queue class"""</span></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__init__</span><span class="params">(self, server, spider, key, serializer=None)</span>:</span></span><br><span class="line">        <span class="keyword">if</span> serializer <span class="keyword">is</span> <span class="literal">None</span>:</span><br><span class="line">            serializer = picklecompat</span><br><span class="line">        <span class="keyword">if</span> <span class="keyword">not</span> hasattr(serializer, <span class="string">'loads'</span>):</span><br><span class="line">            <span class="keyword">raise</span> TypeError(<span class="string">"serializer does not implement 'loads' function: % r"</span></span><br><span class="line">                            % serializer)</span><br><span class="line">        <span class="keyword">if</span> <span class="keyword">not</span> hasattr(serializer, <span class="string">'dumps'</span>):</span><br><span class="line">            <span class="keyword">raise</span> TypeError(<span class="string">"serializer '% s' does not implement 'dumps' function: % r"</span></span><br><span class="line">                            % serializer)</span><br><span class="line">        self.server = server</span><br><span class="line">        self.spider = spider</span><br><span class="line">        self.key = key % &#123;<span class="string">'spider'</span>: spider.name&#125;</span><br><span class="line">        self.serializer = serializer</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">_encode_request</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        obj = request_to_dict(request, self.spider)</span><br><span class="line">        <span class="keyword">return</span> self.serializer.dumps(obj)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">_decode_request</span><span class="params">(self, encoded_request)</span>:</span></span><br><span class="line">        obj = self.serializer.loads(encoded_request)</span><br><span class="line">        <span class="keyword">return</span> request_from_dict(obj, self.spider)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__len__</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Return the length of the queue"""</span></span><br><span class="line">        <span class="keyword">raise</span> NotImplementedError</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">push</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Push a request"""</span></span><br><span class="line">        <span class="keyword">raise</span> NotImplementedError</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">pop</span><span class="params">(self, timeout=<span class="number">0</span>)</span>:</span></span><br><span class="line">        <span class="string">"""Pop a request"""</span></span><br><span class="line">        <span class="keyword">raise</span> NotImplementedError</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">clear</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Clear queue/stack"""</span></span><br><span class="line">        self.server.delete(self.key)</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>首先看一下 <em>encode<em>request() 和 _decode_request() 方法，因为我们需要把一 个 Request 对象存储到数据库中，但数据库无法直接存储对象，所以需要将 Request 序列化转成字符串再存储，而这两个方法就分别是序列化和反序列化的操作，利用 pickle 库来实现，一般在调用 push() 将 Request 存入数据库时会调用 _encode_request() 方法进行序列化，在调用 pop() 取出 Request 的时候会调用 _decode_request() 进行反序列化。 在父类中 __len</em></em>()、push() 和 pop() 方法都是未实现的，会直接抛出 NotImplementedError，因此这个类是不能直接被使用的，所以必须要实现一个子类来重写这三个方法，而不同的子类就会有不同的实现，也就有着不同的功能。 那么接下来就需要定义一些子类来继承 Base 类，并重写这几个方法，那在源码中就有三个子类的实现，它们分别是 FifoQueue、PriorityQueue、LifoQueue，我们分别来看下它们的实现原理。 首先是 FifoQueue：</p>
                <figure class="highlight python">
                  <table>
                    <tr>
                      <td class="gutter">
                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">FifoQueue</span><span class="params">(Base)</span>:</span></span><br><span class="line">    <span class="string">"""Per-spider FIFO queue"""</span></span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__len__</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Return the length of the queue"""</span></span><br><span class="line">        <span class="keyword">return</span> self.server.llen(self.key)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">push</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Push a request"""</span></span><br><span class="line">        self.server.lpush(self.key, self._encode_request(request))</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">pop</span><span class="params">(self, timeout=<span class="number">0</span>)</span>:</span></span><br><span class="line">        <span class="string">"""Pop a request"""</span></span><br><span class="line">        <span class="keyword">if</span> timeout &gt; <span class="number">0</span>:</span><br><span class="line">            data = self.server.brpop(self.key, timeout)</span><br><span class="line">            <span class="keyword">if</span> isinstance(data, tuple):</span><br><span class="line">                data = data[<span class="number">1</span>]</span><br><span class="line">        <span class="keyword">else</span>:</span><br><span class="line">            data = self.server.rpop(self.key)</span><br><span class="line">        <span class="keyword">if</span> data:</span><br><span class="line">            <span class="keyword">return</span> self._decode_request(data)</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>可以看到这个类继承了 Base 类，并重写了 <strong>len</strong>()、push()、pop() 这三个方法，在这三个方法中都是对 server 对象的操作，而 server 对象就是一个 Redis 连接对象，我们可以直接调用其操作 Redis 的方法对数据库进行操作，可以看到这里的操作方法有 llen()、lpush()、rpop() 等，那这就代表此爬取队列是使用的 Redis 的列表，序列化后的 Request 会被存入列表中，就是列表的其中一个元素，<strong>len</strong>() 方法是获取列表的长度，push() 方法中调用了 lpush() 操作，这代表从列表左侧存入数据，pop() 方法中调用了 rpop() 操作，这代表从列表右侧取出数据。 所以 Request 在列表中的存取顺序是左侧进、右侧出，所以这是有序的进出，即先进先出，英文叫做 First Input First Output，也被简称作 Fifo，而此类的名称就叫做 FifoQueue。 另外还有一个与之相反的实现类，叫做 LifoQueue，实现如下：</p>
                <figure class="highlight python">
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                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">LifoQueue</span><span class="params">(Base)</span>:</span></span><br><span class="line">    <span class="string">"""Per-spider LIFO queue."""</span></span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__len__</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Return the length of the stack"""</span></span><br><span class="line">        <span class="keyword">return</span> self.server.llen(self.key)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">push</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Push a request"""</span></span><br><span class="line">        self.server.lpush(self.key, self._encode_request(request))</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">pop</span><span class="params">(self, timeout=<span class="number">0</span>)</span>:</span></span><br><span class="line">        <span class="string">"""Pop a request"""</span></span><br><span class="line">        <span class="keyword">if</span> timeout &gt; <span class="number">0</span>:</span><br><span class="line">            data = self.server.blpop(self.key, timeout)</span><br><span class="line">            <span class="keyword">if</span> isinstance(data, tuple):</span><br><span class="line">                data = data[<span class="number">1</span>]</span><br><span class="line">        <span class="keyword">else</span>:</span><br><span class="line">            data = self.server.lpop(self.key)</span><br><span class="line"></span><br><span class="line">        <span class="keyword">if</span> data:</span><br><span class="line">            <span class="keyword">return</span> self._decode_request(data)</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>与 FifoQueue 不同的就是它的 pop() 方法，在这里使用的是 lpop() 操作，也就是从左侧出，而 push() 方法依然是使用的 lpush() 操作，是从左侧入。那么这样达到的效果就是先进后出、后进先出，英文叫做 Last In First Out，简称为 Lifo，而此类名称就叫做 LifoQueue。同时这个存取方式类似栈的操作，所以其实也可以称作 StackQueue。 另外在源码中还有一个子类实现，叫做 PriorityQueue，顾名思义，它叫做优先级队列，实现如下：</p>
                <figure class="highlight python">
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                      <td class="gutter">
                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">PriorityQueue</span><span class="params">(Base)</span>:</span></span><br><span class="line">    <span class="string">"""Per-spider priority queue abstraction using redis' sorted set"""</span></span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__len__</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Return the length of the queue"""</span></span><br><span class="line">        <span class="keyword">return</span> self.server.zcard(self.key)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">push</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Push a request"""</span></span><br><span class="line">        data = self._encode_request(request)</span><br><span class="line">        score = -request.priority</span><br><span class="line">        self.server.execute_command(<span class="string">'ZADD'</span>, self.key, score, data)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">pop</span><span class="params">(self, timeout=<span class="number">0</span>)</span>:</span></span><br><span class="line">        <span class="string">"""</span></span><br><span class="line"><span class="string">        Pop a request</span></span><br><span class="line"><span class="string">        timeout not support in this queue class</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        pipe = self.server.pipeline()</span><br><span class="line">        pipe.multi()</span><br><span class="line">        pipe.zrange(self.key, <span class="number">0</span>, <span class="number">0</span>).zremrangebyrank(self.key, <span class="number">0</span>, <span class="number">0</span>)</span><br><span class="line">        results, count = pipe.execute()</span><br><span class="line">        <span class="keyword">if</span> results:</span><br><span class="line">            <span class="keyword">return</span> self._decode_request(results[<span class="number">0</span>])</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>在这里我们可以看到 <strong>len</strong>()、push()、pop() 方法中使用了 server 对象的 zcard()、zadd()、zrange() 操作，可以知道这里使用的存储结果是有序集合 Sorted Set，在这个集合中每个元素都可以设置一个分数，那么这个分数就代表优先级。 在 <strong>len</strong>() 方法里调用了 zcard() 操作，返回的就是有序集合的大小，也就是爬取队列的长度，在 push() 方法中调用了 zadd() 操作，就是向集合中添加元素，这里的分数指定成 Request 的优先级的相反数，因为分数低的会排在集合的前面，所以这里高优先级的 Request 就会存在集合的最前面。pop() 方法是首先调用了 zrange() 操作取出了集合的第一个元素，因为最高优先级的 Request 会存在集合最前面，所以第一个元素就是最高优先级的 Request，然后再调用 zremrangebyrank() 操作将这个元素删除，这样就完成了取出并删除的操作。 此队列是默认使用的队列，也就是爬取队列默认是使用有序集合来存储的。</p>
                <h3 id="3-去重过滤"><a href="#3-去重过滤" class="headerlink" title="3. 去重过滤"></a>3. 去重过滤</h3>
                <p>前面说过 Scrapy 的去重是利用集合来实现的，而在 Scrapy 分布式中的去重就需要利用共享的集合，那么这里使用的就是 Redis 中的集合数据结构。我们来看看去重类是怎样实现的，源码文件是 dupefilter.py，其内实现了一个 RFPDupeFilter 类，如下所示：</p>
                <figure class="highlight python">
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                      <td class="gutter">
                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br><span class="line">96</span><br><span class="line">97</span><br><span class="line">98</span><br><span class="line">99</span><br><span class="line">100</span><br><span class="line">101</span><br><span class="line">102</span><br><span class="line">103</span><br><span class="line">104</span><br><span class="line">105</span><br><span class="line">106</span><br><span class="line">107</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">RFPDupeFilter</span><span class="params">(BaseDupeFilter)</span>:</span></span><br><span class="line">    <span class="string">"""Redis-based request duplicates filter.</span></span><br><span class="line"><span class="string">    This class can also be used with default Scrapy's scheduler.</span></span><br><span class="line"><span class="string">    """</span></span><br><span class="line">    logger = logger</span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">__init__</span><span class="params">(self, server, key, debug=False)</span>:</span></span><br><span class="line">        <span class="string">"""Initialize the duplicates filter.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        server : redis.StrictRedis</span></span><br><span class="line"><span class="string">            The redis server instance.</span></span><br><span class="line"><span class="string">        key : str</span></span><br><span class="line"><span class="string">            Redis key Where to store fingerprints.</span></span><br><span class="line"><span class="string">        debug : bool, optional</span></span><br><span class="line"><span class="string">            Whether to log filtered requests.</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        self.server = server</span><br><span class="line">        self.key = key</span><br><span class="line">        self.debug = debug</span><br><span class="line">        self.logdupes = <span class="literal">True</span></span><br><span class="line"></span><br><span class="line"><span class="meta">    @classmethod</span></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">from_settings</span><span class="params">(cls, settings)</span>:</span></span><br><span class="line">        <span class="string">"""Returns an instance from given settings.</span></span><br><span class="line"><span class="string">        This uses by default the key ``dupefilter:&lt;timestamp&gt;``. When using the</span></span><br><span class="line"><span class="string">        ``scrapy_redis.scheduler.Scheduler`` class, this method is not used as</span></span><br><span class="line"><span class="string">        it needs to pass the spider name in the key.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        settings : scrapy.settings.Settings</span></span><br><span class="line"><span class="string">        Returns</span></span><br><span class="line"><span class="string">        -------</span></span><br><span class="line"><span class="string">        RFPDupeFilter</span></span><br><span class="line"><span class="string">            A RFPDupeFilter instance.</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        server = get_redis_from_settings(settings)</span><br><span class="line">        key = defaults.DUPEFILTER_KEY % &#123;<span class="string">'timestamp'</span>: int(time.time())&#125;</span><br><span class="line">        debug = settings.getbool(<span class="string">'DUPEFILTER_DEBUG'</span>)</span><br><span class="line">        <span class="keyword">return</span> cls(server, key=key, debug=debug)</span><br><span class="line"></span><br><span class="line"><span class="meta">    @classmethod</span></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">from_crawler</span><span class="params">(cls, crawler)</span>:</span></span><br><span class="line">        <span class="string">"""Returns instance from crawler.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        crawler : scrapy.crawler.Crawler</span></span><br><span class="line"><span class="string">        Returns</span></span><br><span class="line"><span class="string">        -------</span></span><br><span class="line"><span class="string">        RFPDupeFilter</span></span><br><span class="line"><span class="string">            Instance of RFPDupeFilter.</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        <span class="keyword">return</span> cls.from_settings(crawler.settings)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">request_seen</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Returns True if request was already seen.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        request : scrapy.http.Request</span></span><br><span class="line"><span class="string">        Returns</span></span><br><span class="line"><span class="string">        -------</span></span><br><span class="line"><span class="string">        bool</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        fp = self.request_fingerprint(request)</span><br><span class="line">        added = self.server.sadd(self.key, fp)</span><br><span class="line">        <span class="keyword">return</span> added == <span class="number">0</span></span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">request_fingerprint</span><span class="params">(self, request)</span>:</span></span><br><span class="line">        <span class="string">"""Returns a fingerprint for a given request.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        request : scrapy.http.Request</span></span><br><span class="line"><span class="string"></span></span><br><span class="line"><span class="string">        Returns</span></span><br><span class="line"><span class="string">        -------</span></span><br><span class="line"><span class="string">        str</span></span><br><span class="line"><span class="string"></span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        <span class="keyword">return</span> request_fingerprint(request)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">close</span><span class="params">(self, reason=<span class="string">''</span>)</span>:</span></span><br><span class="line">        <span class="string">"""Delete data on close. Called by Scrapy's scheduler.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        reason : str, optional</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        self.clear()</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">clear</span><span class="params">(self)</span>:</span></span><br><span class="line">        <span class="string">"""Clears fingerprints data."""</span></span><br><span class="line">        self.server.delete(self.key)</span><br><span class="line"></span><br><span class="line">    <span class="function"><span class="keyword">def</span> <span class="title">log</span><span class="params">(self, request, spider)</span>:</span></span><br><span class="line">        <span class="string">"""Logs given request.</span></span><br><span class="line"><span class="string">        Parameters</span></span><br><span class="line"><span class="string">        ----------</span></span><br><span class="line"><span class="string">        request : scrapy.http.Request</span></span><br><span class="line"><span class="string">        spider : scrapy.spiders.Spider</span></span><br><span class="line"><span class="string">        """</span></span><br><span class="line">        <span class="keyword">if</span> self.debug:</span><br><span class="line">            msg = <span class="string">"Filtered duplicate request: %(request) s"</span></span><br><span class="line">            self.logger.debug(msg, &#123;<span class="string">'request'</span>: request&#125;, extra=&#123;<span class="string">'spider'</span>: spider&#125;)</span><br><span class="line">        <span class="keyword">elif</span> self.logdupes:</span><br><span class="line">            msg = (<span class="string">"Filtered duplicate request %(request) s"</span></span><br><span class="line">                   <span class="string">"- no more duplicates will be shown"</span></span><br><span class="line">                   <span class="string">"(see DUPEFILTER_DEBUG to show all duplicates)"</span>)</span><br><span class="line">            self.logger.debug(msg, &#123;<span class="string">'request'</span>: request&#125;, extra=&#123;<span class="string">'spider'</span>: spider&#125;)</span><br><span class="line">            self.logdupes = <span class="literal">False</span></span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>这里同样实现了一个 request_seen() 方法，和 Scrapy 中的 request_seen() 方法实现极其类似。不过这里集合使用的是 server 对象的 sadd() 操作，也就是集合不再是一个简单数据结构了，而是直接换成了数据库的存储方式。 鉴别重复的方式还是使用指纹，指纹同样是依靠 request_fingerprint() 方法来获取的。获取指纹之后就直接向集合添加指纹，如果添加成功，说明这个指纹原本不存在于集合中，返回值 1。代码中最后的返回结果是判定添加结果是否为 0，如果刚才的返回值为 1，那这个判定结果就是 False，也就是不重复，否则判定为重复。 这样我们就成功利用 Redis 的集合完成了指纹的记录和重复的验证。</p>
                <h3 id="4-调度器"><a href="#4-调度器" class="headerlink" title="4. 调度器"></a>4. 调度器</h3>
                <p>Scrapy-Redis 还帮我们实现了配合 Queue、DupeFilter 使用的调度器 Scheduler，源文件名称是 scheduler.py。我们可以指定一些配置，如 SCHEDULER_FLUSH_ON_START 即是否在爬取开始的时候清空爬取队列，SCHEDULER_PERSIST 即是否在爬取结束后保持爬取队列不清除。我们可以在 settings.py 里自由配置，而此调度器很好地实现了对接。 接下来我们看看两个核心的存取方法，实现如下所示：</p>
                <figure class="highlight ruby">
                  <table>
                    <tr>
                      <td class="gutter">
                        <pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br></pre>
                      </td>
                      <td class="code">
                        <pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">enqueue_request</span><span class="params">(<span class="keyword">self</span>, request)</span></span><span class="symbol">:</span></span><br><span class="line">    <span class="keyword">if</span> <span class="keyword">not</span> request.dont_filter <span class="keyword">and</span> <span class="keyword">self</span>.df.request_seen(request)<span class="symbol">:</span></span><br><span class="line">        <span class="keyword">self</span>.df.log(request, <span class="keyword">self</span>.spider)</span><br><span class="line">        <span class="keyword">return</span> False</span><br><span class="line">    <span class="keyword">if</span> <span class="keyword">self</span>.<span class="symbol">stats:</span></span><br><span class="line">        <span class="keyword">self</span>.stats.inc_value(<span class="string">'scheduler/enqueued/redis'</span>, spider=<span class="keyword">self</span>.spider)</span><br><span class="line">    <span class="keyword">self</span>.queue.push(request)</span><br><span class="line">    <span class="keyword">return</span> True</span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">next_request</span><span class="params">(<span class="keyword">self</span>)</span></span><span class="symbol">:</span></span><br><span class="line">    block_pop_timeout = <span class="keyword">self</span>.idle_before_close</span><br><span class="line">    request = <span class="keyword">self</span>.queue.pop(block_pop_timeout)</span><br><span class="line">    <span class="keyword">if</span> request <span class="keyword">and</span> <span class="keyword">self</span>.<span class="symbol">stats:</span></span><br><span class="line">        <span class="keyword">self</span>.stats.inc_value(<span class="string">'scheduler/dequeued/redis'</span>, spider=<span class="keyword">self</span>.spider)</span><br><span class="line">    <span class="keyword">return</span> request</span><br></pre>
                      </td>
                    </tr>
                  </table>
                </figure>
                <p>enqueue_request() 可以向队列中添加 Request，核心操作就是调用 Queue 的 push() 操作，还有一些统计和日志操作。next_request() 就是从队列中取 Request，核心操作就是调用 Queue 的 pop() 操作，此时如果队列中还有 Request，则 Request 会直接取出来，爬取继续，否则如果队列为空，爬取则会重新开始。</p>
                <h3 id="5-总结"><a href="#5-总结" class="headerlink" title="5. 总结"></a>5. 总结</h3>
                <p>那么到现在为止我们就把之前所说的三个分布式的问题解决了，总结如下：</p>
                <ul>
                  <li>爬取队列的实现，在这里提供了三种队列，使用了 Redis 的列表或有序集合来维护。</li>
                  <li>去重的实现，使用了 Redis 的集合来保存 Request 的指纹来提供重复过滤。</li>
                  <li>中断后重新爬取的实现，中断后 Redis 的队列没有清空，再次启动时调度器的 next_request() 会从队列中取到下一个 Request，继续爬取。</li>
                </ul>
                <h3 id="6-结语"><a href="#6-结语" class="headerlink" title="6. 结语"></a>6. 结语</h3>
                <p>以上内容便是 Scrapy-Redis 的核心源码解析。Scrapy-Redis 中还提供了 Spider、Item Pipeline 的实现，不过它们并不是必须使用。 在下一节，我们会将 Scrapy-Redis 集成到之前所实现的 Scrapy 新浪微博项目中，实现多台主机协同爬取。</p>
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